[1]} continued to explore the question of "what differences remain between computer and human vision" based on [2]}.
They used the Evolutionary Algorithm to generate high-confidence adversarial images by iterating over direct-encoded images and CPPN (Compositional Pattern-Producing Network) encoded images, respectively.
They obtained high-confidence adversarial samples (fooling images) using the Evolutionary Algorithm on a LeNet model pre-trained on the MNIST dataset [3]} and on an AlexNet model pre-trained on the ILSVRC 2012 ImageNet dataset [4]}, [5]}, respectively.
